Objective analysis of ARM IOP data: Method and sensitivity

Motivated by the need to obtain accurate objective analysis of field experi mental data to force physical parameterizations in numerical models, this p aper first reviews the existing objective analysis methods and interpolatio n schemes that are used to derive atmospheric wind divergence, vertical vel ocity, and advective tendencies, Advantages and disadvantages of different methods are discussed. It is shown that considerable uncertainties in the a nalyzed products can result from the use of different analysis. The paper t hen describes a hybrid approach to combine the strengths of the regular gri d and the line-integral methods, together with a variational constraining p rocedure for the analysis of field experimental data. In addition to the us e of upper air data, measurements at the surface and at the top of the atmo sphere (TOA) are used to constrain the upper-air analysis to conserve colum n-integrated mass, water, energy, and momentum. Analyses are shown for measurements taken in the Atmospheric Radiation Meas urement Program July 1995 intensive observational period. Sensitivity exper iments are carried our to test the robustness of the analyzed data and to r eveal uncertainties in the analysis. These include sensitivities to the int erpolation schemes, to the types of input data sources, and to the variatio nal constraining procedures. It is shown that the constraining process of u sing additional surface and TOA data significantly reduces the sensitivity of the final data products.